Neural commit message suggester

Proposing git commit messages with neural networks

We present a suggester of git commit messages based on the files diff: by reading the commit patch, the system outputs a message in natural language describing the subject of the commit.
While high level intent guessing is out of the scope of this project, this may provide further insights to a CI system in refusing pull requests with poor commit messages or not explaining the subject matter.

When it comes to commit messages, we all have witnessed the worst of our kind: while code is (hopefully) carefully crafted, the urge to submit our work for peer review can play badly with the helpfulness of the commit message attached (leaving a helpless reviewer in the dark and calling for the developer presence to explain the meaning of the coded feature).
Machine translation techniques come to the rescue, by providing a viable aid to suggesting better commit messages from a golden standard of various situations: by analyzing thousands of commit messages along with their patches, we show that a machine can understand the semantics of a patch thus providing a way to automatically tell good messages from bad messages.
We can employ this in CI environments to rule out insufficiently documented patches or to propose better alternatives to the developers.